class_docstr: Wraps the weight so that in can be sliced with a ``multidim_slice``.
  The value within the slice can be instances of :class:`MaybeWeighted`.
  
  Examples
  --------
  >>> weight = conv2d.weight
  >>> Slicable(weight)[:MaybeWeighted({32: 0.4, 64: 0.6})]
  Tensor of shape (64, 64, 3, 3)
code: def __init__(self, weight: T):
      if not isinstance(weight, np.ndarray) and not torch.is_tensor(
          weight
      ):
          raise TypeError(f"Unsuppoted weight type: {type(weight)}")
      self.weight = weight
  
imports: from __future__ import annotations
  import operator
  from typing import Callable, Iterator, TypeVar, Any, Optional, Tuple, Union, List, Dict, Generic, cast
  import numpy
  import torch
label_desc: Use image node_id 1 to create a new Slicable object from inherited base classes: Generic with example: obj = Slicable(weight)